학술논문

Self-organized Criticality and Scale-free Properties in Emergent Functional Neural Networks
Document Type
Working Paper
Source
Subject
Condensed Matter - Disordered Systems and Neural Networks
Nonlinear Sciences - Adaptation and Self-Organizing Systems
Quantitative Biology - Neurons and Cognition
Language
Abstract
Recent studies on the complex systems have shown that the synchronization of oscillators including neuronal ones is faster, stronger, and more efficient in the small-world networks than in the regular or the random networks, and many studies are based on the assumption that the brain may utilize the small-world and scale-free network structure. We show that the functional structures in the brain are self-organized to both the small-world and the scale-free networks by synaptic re-organization by the spike timing dependent synaptic plasticity (STDP), which is hardly achieved with conventional Hebbian learning rules. We show that the balance between the excitatory and the inhibitory synaptic inputs is critical in the formation of the functional structure, which is found to lie in a self-organized critical state.
Comment: 4 pages, 3 figures